Long Term Evolution (LTE)
Third-generation mobile systems (3G) based on WCDMA radio-access technology are being deployed on a broad scale all around the world. A first step in enhancing or evolving this technology entails introducing High-Speed Downlink Packet Access (HSDPA) and an enhanced uplink, also referred to as High Speed Uplink Packet Access (HSUPA), giving a radio-access technology that is highly competitive.
In order to be prepared for further increasing user demands and to be competitive against new radio access technologies, 3GPP introduced a new mobile communication system which is called Long Term Evolution (LTE). LTE is designed to meet the carrier needs for high speed data and media transport as well as high capacity voice support to the next decade. The ability to provide high bit rates is a key measure for LTE.
The work item (WI) specification on Long-Term Evolution (LTE) called Evolved UMTS Terrestrial Radio Access (UTRA) and UMTS Terrestrial Radio Access Network (UTRAN) is to be finalized as Release 8 (LTE Rel. 8). The LTE system represents efficient packet-based radio access and radio access networks that provide full IP-based functionalities with low latency and low cost. In LTE, scalable multiple transmission bandwidths are specified such as 1.4, 3.0, 5.0, 10.0, 15.0, and 20.0 MHz, in order to achieve flexible system deployment using a given spectrum. In the downlink, Orthogonal Frequency Division Multiplexing (OFDM) based radio access was adopted because of its inherent immunity to multipath interference (MPI) due to a low symbol rate, the use of a cyclic prefix (CP) and its affinity to different transmission bandwidth arrangements. Single-carrier frequency division multiple access (SC-FDMA) based radio access was adopted in the uplink, since provisioning of wide area coverage was prioritized over improvement in the peak data rate considering the restricted transmit power of the user equipment (UE). Many key packet radio access techniques are employed including multiple-input multiple-output (MIMO) channel transmission techniques and a highly efficient control signaling structure is achieved in LTE Rel. 8/9.
LTE Architecture
The overall architecture is shown in FIG. 1 and a more detailed representation of the E-UTRAN architecture is given in FIG. 2. The E-UTRAN consists of eNodeB, providing the E-UTRA user plane (PDCP/RLC/MAC/PHY) and control plane (RRC) protocol terminations towards the user equipment (UE). The eNodeB (eNB) hosts the Physical (PHY), Medium Access Control (MAC), Radio Link Control (RLC), and Packet Data Control Protocol (PDCP) layers that include the functionality of user-plane header-compression and encryption. It also offers Radio Resource Control (RRC) functionality corresponding to the control plane. It performs many functions including radio resource management, admission control, scheduling, enforcement of negotiated uplink Quality of Service (QoS), cell information broadcast, ciphering/deciphering of user and control plane data, and compression/decompression of downlink/uplink user plane packet headers. The eNodeBs are interconnected with each other by means of the X2 interface.
The eNodeBs are also connected by means of the S1 interface to the EPC (Evolved Packet Core), more specifically to the MME (Mobility Management Entity) by means of the S1-MME and to the Serving Gateway (SGW) by means of the S1-U. The S1 interface supports a many-to-many relation between MMES/Serving Gateways and eNodeBs. The SGW routes and forwards user data packets, while also acting as the mobility anchor for the user plane during inter-eNodeB handovers and as the anchor for mobility between LTE and other 3GPP technologies (terminating S4 interface and relaying the traffic between 2G/3G systems and PDN GW). For idle state user equipments, the SGW terminates the downlink data path and triggers paging when downlink data arrives for the user equipment. It manages and stores user equipment contexts, e.g. parameters of the IP bearer service, network internal routing information. It also performs replication of the user traffic in case of lawful interception.
The MME is the key control-node for the LTE access-network. It is responsible for idle mode user equipment tracking and paging procedure including retransmissions. It is involved in the bearer activation/deactivation process and is also responsible for choosing the SGW for a user equipment at the initial attach and at time of intra-LTE handover involving Core Network (CN) node relocation. It is responsible for authenticating the user (by interacting with the HSS). The Non-Access Stratum (NAS) signaling terminates at the MME and it is also responsible for generation and allocation of temporary identities to user equipments. It checks the authorization of the user equipment to camp on the service provider's Public Land Mobile Network (PLMN) and enforces user equipment roaming restrictions. The MME is the termination point in the network for ciphering/integrity protection for NAS signaling and handles the security key management. Lawful interception of signaling is also supported by the MME. The MME also provides the control plane function for mobility between LTE and 2G/3G access networks with the S3 interface terminating at the MME from the SGSN. The MME also terminates the S6a interface towards the home HSS for roaming user equipments.
Component Carrier Structure in LTE (Release 8)
The downlink component carrier of a 3GPP LTE (Release 8) is subdivided in the time-frequency domain in so-called subframes. In 3GPP LTE (Release 8) each subframe is divided into two downlink slots as shown in FIG. 3, wherein the first downlink slot comprises the control channel region (PDCCH region) within the first OFDM symbols. Each subframe consists of a give number of OFDM symbols in the time domain (12 or 14 OFDM symbols in 3GPP LTE (Release 8)), wherein each OFDM symbol spans over the entire bandwidth of the component carrier. The OFDM symbols thus each consists of a number of modulation symbols transmitted on respective NRBDL×NscRB subcarriers as also shown in FIG. 4.
Assuming a multi-carrier communication system, e.g. employing OFDM, as for example used in 3GPP Long Term Evolution (LTE), the smallest unit of resources that can be assigned by the scheduler is one “resource block”. A physical resource block is defined as NsymbDL consecutive OFDM symbols in the time domain and NscRB consecutive subcarriers in the frequency domain as exemplified in FIG. 4. In 3GPP LTE (Release 8), a physical resource block thus consists of NsymbDL×NscRB resource elements, corresponding to one slot in the time domain and 180 kHz in the frequency domain (for further details on the downlink resource grid, see for example 3GPP TS 36.211, “Evolved Universal Terrestrial Radio Access (E-UTRA); Physical Channels and Modulation (Release 8)”, version 8.9.0 or 9.0.0, section 6.2, available at http://www.3gpp.org and incorporated herein by reference).
The term “component carrier” refers to a combination of several resource blocks. In future releases of LTE, the term “component carrier” is no longer used; instead, the terminology is changed to “cell”, which refers to a combination of downlink and optionally uplink resources. The linking between the carrier frequency of the downlink resources and the carrier frequency of the uplink resources is indicated in the system information transmitted on the downlink resources.
Further Advancements for LTE (LTE-A)
The frequency spectrum for IMT-Advanced was decided at the World Radiocommunication Conference 2007 (WRC-07). Although the overall frequency spectrum for IMT-Advanced was decided, the actual available frequency bandwidth is different according to each region or country. Following the decision on the available frequency spectrum outline, however, standardization of a radio interface started in the 3rd Generation Partnership Project (3GPP). At the 3GPP TSG RAN #39 meeting, the Study Item description on “Further Advancements for E-UTRA (LTE-Advanced)” was approved. The study item covers technology components to be considered for the evolution of E-UTRA, e.g. to fulfill the requirements on IMT-Advanced. Two major technology components which are currently under consideration for LTE-A are described in the following.
Carrier Aggregation in LTE-A for Support of Wider Bandwidth
The bandwidth that the LTE-Advanced system is able to support is 100 MHz, while an LTE system can only support 20 MHz. Nowadays, the lack of radio spectrum has become a bottleneck of the development of wireless networks, and as a result it is difficult to find a spectrum band which is wide enough for the LTE-Advanced system. Consequently, it is urgent to find a way to gain a wider radio spectrum band, wherein a possible answer is the carrier aggregation functionality.
In carrier aggregation, two or more component carriers (component carriers) are aggregated in order to support wider transmission bandwidths up to 100 MHz. Several cells in the LTE system are aggregated into one wider channel in the LTE-Advanced system which is wide enough for 100 MHz even though these cells in LTE are in different frequency bands.
All component carriers can be configured to be LTE Rel. 8/9 compatible, at least when the aggregated numbers of component carriers in the uplink and the downlink are the same. Not all component carriers aggregated by a user equipment may necessarily be Rel. 8/9 compatible. Existing mechanism (e.g. barring) may be used to avoid Rel-8/9 user equipments to camp on a component carrier.
A user equipment may simultaneously receive or transmit one or multiple component carriers (corresponding to multiple serving cells) depending on its capabilities. A LTE-A Rel. 10 user equipment with reception and/or transmission capabilities for carrier aggregation can simultaneously receive and/or transmit on multiple serving cells, whereas an LTE Rel. 8/9 user equipment can receive and transmit on a single serving cell only, provided that the structure of the component carrier follows the Rel. 8/9 specifications.
Channel Quality Reporting
The principle of link adaptation is fundamental to the design of a radio interface which is efficient for packet-switched data traffic. Unlike the early versions of UMTS (Universal Mobile Telecommunication System), which used fast closed-loop power control to support circuit-switched services with a roughly constant data rate, link adaptation in LTE adjusts the transmitted data rate (modulation scheme and channel coding rate) dynamically to match the prevailing radio channel capacity for each user.
For the downlink data transmissions in LTE, the eNodeB typically selects the modulation scheme and code rate (MCS) depending on a prediction of the downlink channel conditions. An important input to this selection process is the Channel State Information (CSI) feedback transmitted by the User Equipment (UE) in the uplink to the eNodeB.
Channel state information is used in a multi-user communication system, such as for example 3GPP LTE to determine the quality of channel resource(s) for one or more users. In general, in response to the CSI feedback the eNodeB can select between QPSK, 16-QAM and 64-QAM schemes and a wide range of code rates. This CSI information may be used to aid in a multi-user scheduling algorithm to assign channel resources to different users, or to adapt link parameters such as modulation scheme, coding rate or transmit power, so as to exploit the assigned channel resources to its fullest potential.
The CSI is reported for every component carrier, and, depending on the reporting mode and bandwidth, for different sets of subbands of the component carrier. A channel resource may be defined as a “resource block” as exemplary illustrated in FIG. 4 where a multi-carrier communication system, e.g. employing OFDM as for example discussed in the LTE work item of 3GPP, is assumed. More generally, it may be assumed that a resource block designates the smallest resource unit on an air interface of a mobile communication that can be assigned by a scheduler. The dimensions of a resource block may be any combination of time (e.g. time slot, subframe, frame, etc. for time division multiplex (TDM)), frequency (e.g. subband, carrier frequency, etc. for frequency division multiplex (FDM)), code (e.g. spreading code for code division multiplex (CDM)), antenna (e.g. Multiple Input Multiple Output (MIMO)), etc. depending on the access scheme used in the mobile communication system.
Assuming that the smallest assignable resource unit is a resource block, in the ideal case channel quality information for each and all resource blocks and each and all users should be always available. However, due to constrained capacity of the feedback channel this is most likely not feasible or even impossible. Therefore, reduction or compression techniques are required so as to reduce the channel quality feedback signalling overhead, e.g. by transmitting channel quality information only for a subset of resource blocks for a given user.
In 3GPP LTE, the smallest unit for which channel quality is reported is called a subband, which consists of multiple frequency-adjacent resource blocks.
As described before, user equipments will usually not perform and report CSI measurements on configured but deactivated downlink component carriers but only radio resource management related measurements like RSRP (Reference Signal Received Power) and RSRQ (Reference Signal Received Quality). When activating a downlink component carrier, it's important that the eNodeB acquires quickly CSI information for the newly activated component carrier(s) in order to being able to select an appropriate MCS for efficient downlink scheduling. Without CSI information the eNodeB doesn't have knowledge about the user equipment's downlink channel state and would most likely select a too aggressive or too conservative MCS for downlink data transmission, both of which would in turn lead to resource utilization inefficiency due to required retransmissions or unexploited channel capacity.
Channel State Information Feedback Elements
Commonly, mobile communication systems define special control signalling that is used to convey the channel quality feedback. In 3GPP LTE, there exist three basic elements which may or may not be given as feedback for the channel quality. These channel quality elements are:                MCSI: Modulation and Coding Scheme Indicator, sometimes referred to as Channel Quality Indicator (CQI) in the LTE specification        PMI: Precoding Matrix Indicator        RI: Rank Indicator        
The MCSI suggests a modulation and coding scheme that should be used for transmission, while the PMI points to a pre-coding matrix/vector that is to be employed for spatial multiplexing and multi-antenna transmission (MIMO) using a transmission matrix rank that is given by the RI. Details about the involved reporting and transmission mechanisms are given in the following specifications to which it is referred for further reading (all documents available at http://www.3gpp.org and incorporated herein by reference):                3GPP TS 36.211, “Evolved Universal Terrestrial Radio Access (E-UTRA); Physical channels and modulation”, version 10.0.0, particularly sections 6.3.3, 6.3.4,        3GPP TS 36.212, “Evolved Universal Terrestrial Radio Access (E-UTRA); Multiplexing and channel coding”, version 10.0.0, particularly sections 5.2.2, 5.2.4, 5.3.3,        3GPP TS 36.213, “Evolved Universal Terrestrial Radio Access (E-UTRA); Physical layer procedures”, version 10.0.1, particularly sections 7.1.7, and 7.2.        
In 3GPP LTE, not all of the above identified three channel quality elements are reported at any time. The elements being actually reported depend mainly on the configured reporting mode. It should be noted that 3GPP LTE also supports the transmission of two codewords (i.e. two codewords of user data (transport blocks) may be multiplexed to and transmitted in a single subframe), so that feedback may be given either for one or two codewords. Some details are provided in the next sections and in Table 1 below for an exemplary scenario using a 20 MHz system bandwidth. It should be noted that this information is based on 3GPP TS 36.213, section 7.2.1 mentioned above.
Heterogeneous Networks
In the coming years, operators will begin deploying a new network architecture termed Heterogeneous Networks (HetNet). A typical HetNet deployment as currently discussed within 3GPP consists of macro and pico cells. Pico cells are formed by low power eNBs that may be advantageously placed at traffic hotspots in order to offload traffic from macro cells. Macro and pico eNBs implement the scheduling independently from each other. The mix of high power macro cells and low power pico cells can provide additional capacity and improved coverage.
Pico Cells can be further provided with cell rage expansion (CRE) as a means to increase the throughput performance in such deployments. A UE connects to a macro eNB only if the received power is at least G dB larger than the received power from the strongest pico eNB, where G is the semi-statically configured CRE bias. Typical values are expected to range from 0 to 20 dB.
FIG. 5 illustrates such a HetNet scenario where various pico cells are provided in the area of one macro cell. The pico cells are depicted with two edges where one edge refers to the pico cell edge without CRE and the other to the pico cells with CRE. Various UEs are shown located in the various cells.
However, the additional capacity provided by the smaller cells may be lost due to signal interference experienced by the UEs in the pico cells. The macro eNB is the single dominant interferer for pico UEs, i.e. for UEs being connected to the pico eNB. This is especially true for pico UEs at the cell edge when using CRE.
Furthermore, the interference problem is aggravated when multiple antenna transmissions are used, as will be explained in the following.
Multiple Antenna System
Multiple Input Multiple Output (MIMO) systems form an essential part of LTE in order to achieve the ambitious requirements for throughput and spectral efficiency. Multiple-input and multiple-output is the use of multiple antennas at both the transmitter and receiver to improve communication performance. It is one of several forms of smart antenna technology. Note that the terms input and output refer to the radio channel carrying the signal, not to the devices having antennas.
From a high-level perspective, MIMO can be sub-divided into three main categories, beamforming, spatial multiplexing and diversity coding.
MIMO transmissions are in general based on precoding which can be seen as multi-stream beamforming, in the narrowest definition. In more general terms, it is considered to be all spatial processing that occurs at the transmitter. Beamforming takes advantage of interference to change the directionality of the transmitted signal. When transmitting, a beamformer controls the phase and relative amplitude of the signal at each transmitter, in order to create a pattern of constructive and destructive interference in the wavefront.
In single-layer beamforming, the same signal is emitted from each of the transmit antennas with appropriate phase (and sometimes gain) weighting such that the signal power is maximized at the receiver input. The benefits of beamforming are to increase the received signal power level, by making signals emitted from different antennas add up constructively, and to reduce the multipath fading effect; this effect is known as beamforming gain. In the absence of scattering, beamforming results in a well defined directional pattern, but in typical cellular deployments conventional beams are not a good analogy. When there are multiple receivers (mobile terminals) in the system, superposition of multiple transmit beams can be performed if the receives have sufficient spatial separation. Precoding for beamforming requires knowledge of channel state information (CSI) at the transmitter in order to provide optimum adaptation to the channel. Note that single-layer beamforming does in general not require multiple receive antennas on the mobile terminal side.
Spatial multiplexing requires multiple transmit and receive antennas. In spatial multiplexing, a high rate signal is split into multiple lower rate streams and each stream is transmitted on a spatial layer which is mapped onto the set of transmit antennas in the same frequency channel. If these signals arrive at the receiver antenna array with sufficiently different spatial signatures, the receiver can separate these streams into (almost) parallel channels. Spatial multiplexing is a very powerful technique for increasing channel capacity at higher signal-to-noise ratios (SNR). The maximum number of spatial streams is limited by the lesser in the number of antennas at the transmitter or receiver. Spatial multiplexing can be used with or without transmit channel knowledge. Spatial multiplexing can also be used for simultaneous transmission to multiple receivers (mobile terminals), known as multi-user MIMO. By scheduling receivers with different spatial signatures, good separability can be assured.
When there is no channel knowledge at the transmitter, diversity coding techniques can be used. In diversity methods, a single data stream (unlike multiple streams in spatial multiplexing) is transmitted, but the signal is coded using techniques called space-time coding. The signal is emitted from each of the transmit antennas with full or near orthogonal coding. Diversity coding exploits the independent fading in the multiple antenna links to enhance signal diversity. Because there is no channel knowledge on the transmitter side, there is no beamforming gain from diversity coding.
Spatial multiplexing can also be combined with beamforming if the channel is known at the transmitter or combined with diversity coding if increased decoding reliability is required.
Precoding
In case of downlink MIMO, each base station (eNB) perform precoding on the transmit antennas to adapt the data transmission towards the mobile stations to the current radio channel conditions. In case of a radio channel without any reflections this would correspond to steering the transmission beam into the direction of the receiving mobile terminal. This is achieved by multiplying the signal vector with a precoding matrix W before transmission. With codebook based closed-loop MIMO the mobile terminal estimates the radio channel and selects the optimum precoding matrix W that is selected from a predefined codebook which is known at base station and mobile terminal side. The optimum precoding matrix is the one which offers maximum capacity. The precoding matrices are identified by Precoding Matrix Indicator (PMI) values corresponding to codebook indices according to the corresponding Tables in Chapter 6.3.4.2.3 “Codebook for precoding” of 3GPP document TS 36.211 v10.0.0. As apparent from the above-mentioned tables, the PMI may be 2 or 3 bits long depending on the antenna ports used for transmission and the associated rank indicator (RI).
This feedback is provided to the base station. Depending on the available bandwidth, this information is made available per resource block or group of resource blocks, since the optimum precoding matrix may vary between resource blocks. The network may configure a subset of the codebook that the mobile terminal is able to select from.
The scheduler in the base station selects the precoding matrix thus mainly based on the radio channel characteristics between the base station and the mobile station. Without taking into account which precoding matrices are used in the neighbouring cells, the power radiation patterns (beams) formed by the different cells may collide with each other, resulting in substantial intercell-interference for the cell-edge users. PMI coordination will be explained below.
Intercell Interference and Coordination
Cell-edge users usually have relatively low received signal strength and suffer from strong intercell interference. Boosting the transmission power may increase the received signal strength, but will also create a stronger intercell interference to other cell's cell-edge users and hence reduces their throughput. It is thus important to provide intercell and intracell interference mitigation.
In multi-antenna transmissions with precoding on the interferer side, mobile terminals in the interfered cell may be strongly affected by the use of different precoding matrices in the interfering base station.
The basic interference impact factors are:                Very high average interference level        Very high SINR (CQI) estimation uncertainty due to strong interference flashlight effect        
The Interference Flashlight Effect refers to the effect that each precoding matrix that is used by the interfering base station (described by an Interferer Precoding Matrix Indicator—IPMI) yields a different interference power level on the interference victim mobile terminal side. Since the interferer uses different IPMIs at different times (depending on the multiuser scheduling), the interference victim mobile terminal experiences strong interference fluctuations depending on the IPMIs used by the interference source (interferer base station). These fluctuations are known as the flashlight effect and can result in severe uncertainty concerning the interference level estimation on the victim emobile terminal side.
In order to improve the throughput performance of cell-edge mobile terminals, the interference impact has to be reduced on the resource on which these mobile terminals are scheduled for downlink transmission. The objective of Inter-Cell Interference Coordination (ICIC) is to maximize the multi-cell throughput subject to power constraints, inter-cell signaling limitations, fairness objectives and minimum bit rate requirements.
One solution for interference mitigation is to use subframe patterns with different interference statistics. The concept of creating different interference patterns (e.g. different average interference power levels) of different subframe sets is supported by restricted interference measurements on configured subframe sets as specified in 3GPP RAN1:                Reporting processes for different subframe sets (e.g. Almost Blank Subframe (ABS), non-ABS)        Reports are based on average estimated interference level for a reference resource        
The channel quality is reported to the serving base station (eNB) in form of CQI (Channel Quality Indicator) reports which correspond to a quantization of the expected SINR level on the receiver side. However, CQI reports for different subframe sets provide no information about expected variability of the interference power level (i.e. flashlight effect); only the average interference power level is taken into account.
Importantly, a strong variability of the interference power level (i.e. flashlight effect) can significantly increase the Block Error Rate (BLER) on the receiver side which results in reduced spectral efficiency.
The Best Companion concept is known to mitigate interference, introducing additional codebook-based channel state information in addition to best weight indices (i.e. PMI) that are exchanged between sites. In particular, the mobile terminals (UEs) measure the channel and report the best beam index (rank1 PMI) for their serving base station, i.e. the codebook index of the own transmit weight which maximises the SINR at the receiver output (depending on receiver algorithm supported by mobile terminal), taking into account noise and inter-cell interference. The mobile terminals report so-called best-companion indexes (BCI) for the serving base station, i.e. the codebook index of a potential co-scheduled interferer which maximises the SINR at the receiver output, e.g. a linear MMSE receive matrix which is calculated based on PMI and candidate BCI. The mobile terminals report the CQI for the case that the BCIs are not used. For the case that the best BCIs are used a delta-CQI is reported. In order to minimize intra-cell interference, based on this additional information, for dual stream MU-MIMO, the base station now can pair two mobile terminals n, m, where the PMI of m is the BCI of n, and vice versa. As a result, spectral efficiency will be increased.
Another approach to reduce inter-cell interference is the restriction of precoding matrices in the interfering eNBs. PMI coordination (restriction or recommendation) has been adopted to mitigate inter-cell interference from adjacent cells especially for codebook based closed-loop MIMO systems. Multi-cell coordination of beamforming requires channel knowledge at the transmitter, including the knowledge of interfering neighbour cells (base stations). The interfering base station restricts the precoding based on feedback reports from the interference victim mobile terminal (UEs).
The Worst Companion Index (WCI) is known from the prior art where its feedback efficiently provides information using precoding codebook indices. The UEs measure the channels from a set of dominant interfering cells (base stations), and report the cell and the worst-companion (i.e. strongest interference precoder) PMIs (WCI) for the set of interfering cells. One WCI is thus the tuple of a cell identifier and a precoding matrix indicator (Interferer PMI). Additionally, it may provide the classical channel quality indicator connected to the serving link of the interference victim mobile terminal as well as a delta-CQI, which indicates the estimated gain in case the reported WCI is not used by the interfering neighbour cell (e.g. reflecting the difference in mean signal-to-interference-and-noise ratio, SINR, with and without the WCI). In order to minimize inter-cell interference based on this additional information, beam coordination can now occur. Exemplary, for WCI-reporting a centralized scheduler over low latency backhaul can now schedule users (mobile terminals) of different cells such that on a given time-frequency resource, no interference from reported WCIs will occur, thus reducing the overall interference of the system. As a result, especially cell-edge user throughput will be increased and also spectral efficiency of the system.
At the interferer base station the precoding matrix usage is restricted based on the Worst Companion Index report from the interference victim mobile terminals. An interference victim mobile terminal informs the network about the “worst” PMIs used by the interferer base station causing the highest expected interference at the UE. Of course, different mobile terminals may report different WCI depending on their location. In said case, a restriction applied at the interferer base station is based on a union of the reported WCIs of all involved mobile terminals.
The PMI (IPMI) restrictions based on the WCI reports from the interference victim mobile terminals (UEs) prevent the interferer base station (eNB) from using those IPMIs yielding the maximum inteference at the victim mobile terminal. However, WCI reporting does not necessarily result in IPMI restriction with minimum flashlight effect since the focus of this concept is on minimizing the average interference power level and not flashlight reduction. In particular, the “bad” high interference IPMIs for one victim mobile terminal might be a “good” low interference IPMI for another victim mobile terminal. Furthermore, the average SINR might still not be reduced significantly. Also, the SINR estimation uncertainty (i.e. the flashlight effect) based on the CQI measurements can be still very high or even be increased due to the IPMI restriction based on WCI reporting.
This will be exemplified in FIGS. 6 and 7, illustrating the measurement results at the interference victim mobile terminal side as to six different precoders a-f of the interfering base station and their interference power level caused at the mobile terminal (UE). It is assumed that three different UEs 1-3 are located at one cell, and experience inter-cell interference from a neighbour cell, the level of interference depending on the interference precoding matrix (IPMI) used by the base station (eNB) of the neighbour cell. FIG. 6 further illustrates the worst precoding matrix (i.e. WCI) that are reported by the UEs to the network. Accordingly, UE1 reports precoding matrix c, UE2 reports precoding matrix b, and UE3 reports precoding matrix e. As a result of the WCI reporting, the interfering eNB is instructed to restrict the use of precoding matrices (i.e. PMI restriction) such that precoding matrices c, b and e are not used. The resulting inter-cell inteference after PMI (IPMI) restriction is depicted in FIG. 7 for each UE. As apparent therefrom, the interference flashlight effect, resulting from the strongly varying interference level of the various (remaining) precoders, is not significantly reduced.
In a typical heterogeneous network (HetNet) scenario consisting of macro and pico cells (base station), the effective interference power level on the receiver side (I) can be separated into the contribution from a dominant interferer cell (ID) and the contribution from the remaining interferer cells (IR). Both interference power contributions are time-dependent stochastic processes.I(t)=ID(t)+IR(t)  (1)
The following can be assumed for a typical HetNet scenarios, especially as depicted in FIG. 5:ID(t)>>IR(t)  (2)
Hence, it is reasonable to focus on the interference statistics estimation from the dominant interfering cell (base station). Under the assumption that a dominant interferer uses only a restricted set of precoding matrices, also the interference power levels from that interferer are limited to a certain set of power levels. It is assumed that the interference channel state of the dominant interferer is known on the interference victim mobile terminal side due to measurements of reference symbols (CRS or CSI-RS in case of an LTE system) of the interfering base station.
The interference power level contribution from each single dominant interferer cell (base station) is determined by a function of the interference channel state defined by the M×N matrix HD, where M is the number of receiver antenna ports and N is the number of transmit antenna ports, and the N×L precoding matrix WD, where L is the number of transmitted layers. The precoding matrix WD consists of L column (beamforming) vectors wDi, where each column is the precoding for spatial layer i. The time dependent (depending on subframe n) relation for the interference power level at the receiver input of the interference victim mobile terminal is then given by
                                          I            D                    ⁡                      (            n            )                          =                              ∑                          l              =              1                                      L              ⁡                              (                n                )                                              ⁢                                                                                                        H                    D                                    ⁡                                      (                    n                    )                                                  ·                                                      w                                          D                      i                                                        ⁡                                      (                    n                    )                                                                                      2                                              (        3        )            where ∥HD(n)∥ is the Frobenius Norm of the channel matrix HD(n). L(n) is the number of spatial layers used by the interferer in subframe n.
In general, mobile terminal has to estimate the expected interference power level for data transmissions in subframe n+1 based on measurements in previous subframes.
A typical approach where the estimated interference power level for subframe n+1 is given by the average of the measured interference power levels of the previous S subframes:
                                          I            ~                    ⁡                      (                          n              +              1                        )                          =                              1            S                    ⁢                                    ∑                              i                =                                  n                  -                  S                                            n                        ⁢                          I              ⁡                              (                n                )                                                                        (        4        )            
This approach which is currently used for the channel quality (CQI) reporting in LTE exhibits the following inherent problems:
a) It cannot be distinguished between impact of dominant and remaining interferers.
b) The measuring mobile terminal does not know which precoding matrix (IPMI) has been used by the interferer in which subframe.
c) The measuring mobile terminal cannot distinguish between impact of the channel state and the impact of interference precoding matrix (IPMI) on the interference power level in measured subframes.
The above presented concepts to mitigate inter-cell/intra-cell interference do not take into account the flashlight effect, in other words, the effect that the inter-cell interference may change significantly depending on the precoding matrix used by the interfering base station. This may lead to “wrong” scheduling decisions at the serving base station of the interference victim mobile terminal. This will be explained in more detail below.
Impact of Flashlight Effect
The negative impact of the flashlight effect on scheduling decisions at the serving base station shall be illustrated using two different scenarios.
For ease of explanation the following simple scenario is assumed as illustrated in FIG. 8 Two mobile terminals (UEs), UE1 and UE2, are located in the network of base station 1 (eNB1). A neighbour cell controlled by base station 2 (eNB2) causes inter-cell interference at the cell of base station 1.
UE1 and UE2 each measure the radio channel and report the CQI corresponding to a certain nominal bitrate under the assumption of no transmission errors to the serving eNB1. As apparent from the table of FIG. 9, UE1 measures a mean SINR of 8 dB and reports a quantized CQI of 9 which corresponds to a nominal bitrate of 1.92 bits/symbol under the assumption of a block error rate (BLER) of 0%. UE2 measures a mean SINR of 10 dB and reports a quantized CQI of 10 which corresponds to a nominal bitrate of 2.73 bits/symbol. Correspondingly, eNB1 would schedule UE2 with the higher CQI for the corresponding radio resource to which the CQI refers. However, due to a strong flashlight effect, scheduling UE2 results in an increased BLER of 37% and a throughput of 1.72 (bits/symbol), whereas scheduling UE1 would have resulted in a BLER of 5% and a throughput of 1.82 (bits/symbol). Thus, though UE2 was selected due to the higher reported CQI level, scheduling UE1 would have provided a higher throughput and thus a higher spectral efficiency.
Similarly, in another constellation as depicted in FIG. 10, both UEs measure a mean SINR of 10 dB and consequently report a CQI of 10. As apparent, the CQI reporting does not provide any preference and consequently the base station scheduler may select UE1 and UE2 arbitrarily. However, as shown in FIG. 10, the throughputs achievable by UE1 and UE2 differ significantly, 1.72 vs 2.59.
In another scenario it is assumed that particular IPMI restrictions are applied to particular subframe sets of a radio frame by the interfering base station (eNB). In more detail, the interferer eNB2 of FIG. 8 uses for a first subframe set a first set of precoding matrices, and for a second subframe set it uses a second set of precoding matrices out of all available precoding matrices (PMIs). This is depicted in FIG. 11. The victim UE however does not know which interferer precoding matrix exactly is used by the interfering eNB for a particular subframe.
FIG. 12 illustrates the results of the interference measurements at the victim mobile terminal (UE) for the two different set of interferer precoding matrices, IPMI set A and IMPI set B of FIG. 11. Assuming that both IPMI sets consist of four different precoding matrices each, the mobile terminal measures the interference levels as depicted in FIG. 12. As apparent therefrom, the average interference level measured for IPMI set A is lower than the one estimated for IPMI set B. The average interference level is the basis of the classic CQI report transmitted to the base station (eNB). Thus, IMPI set A (used by eNB2 for subframe set A) seems to be more beneficial than IMPI set B (used by eNB2 for subframe set B). eNB1 now has to decide on which subframe the UEs should be scheduled to maximize the throughput and the spectral efficiency. Consequently, eNB1 would estimate that interference levels at subframes of subframe set A are expected to be lower than for the subframes of the other subframe set B. Thus, eNB1 would schedule UEs preferably at the resources of subframe set A to avoid the higher average interference level in subframe set B caused by the IPMI set B. However, subframe set B would actually be a better choice due to the lower interference variance (i.e. flashlight effect).
FIG. 13 illustrates interference level graphs for four different IPMIs out of a particular IPMI set. The UE measures particular interference samples during a measurement window in order to estimate the interference statistics within the transmission window in which each IPMI might be used with the same probability. As apparent from FIG. 13, six samples are taken at different timings in the measurement window. A sample corresponds to a PDSCH transmission in the interfering cell with an unknown IPMI. Different IPMI were used by the interfering eNB at the point of time where the samples are taken by the measuring interference victim UE. It is assumed that two samples are taken for IPMI a, b and c, whereas no sample was taken for IPMI d, since same was not used by the interfering eNB within the measurement window. This results in a measured interference variability (range) as depicted in FIG. 13, referring to the min and max of the measurement interference level of the various samples. This measured interference variability could be taken as an estimation for the transmission window.
Further marked in FIG. 13 is the real interference variability (range) that may be experienced in the transmission window, which depends on the min and max of the interference graphs in the transmission window. As apparent, the interference estimation for the transmission window significantly differs from the actual interference variability; flashlight effect is actually much stronger than can be expected from the measurement samples in the measurement window.